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Tracking the decisions of others with the own mind

Objective

A core research question in cognitive neuroscience and many other disciplines is to understand how humans interpret the behavior of others. Despite the plethora of empirical work on human Theory of Mind, we still lack a computationally and neurobiologically plausible model. The goal of the current project is to fill this gap by leveraging our extensive knowledge of decision making, which has been formalized as a process of evidence accumulation. Thus, my central hypothesis is that humans utilize their own evidence-accumulation machinery to track others’ minds and to infer their hidden beliefs and preferences. Importantly, my theory goes far beyond previous accounts (e.g., the mirror neuron system), as it specifies not only how we observe others, but also how we predict and learn from their decisions.

I will subject this hypothesis to a series of studies that test its behavioral, physiological and neurobiological implications. Thereto, I will employ cutting-edge cognitive neuroscience tools, including cognitive modeling, eye tracking, functional magnetic resonance imaging, and electroencephalography (EEG). Moreover, I will use EEG hyperscanning to probe the synchronization of brain signals related to evidence accumulation in interacting people. Finally, I will develop a multi-agent artificial intelligence (AI) system that can infer the hidden beliefs of other agents on the basis of their decision processes. I will then show that this AI system provides superior performance in coordinating its actions with human partners.

The multi-modal and mathematically rigorous approach of TrackingMinds will advance our understanding of human mentalizing abilities profoundly. Thereby, it will stimulate further research and applications. First, it can help to devise better interactive AI systems. Second, it has strong implications for equilibrium predictions in economic theory. Third, it can foster new interventions of social mental disorders such as autism and social anxiety.

Field of science

  • /natural sciences/biological sciences/neurobiology/cognitive neuroscience
  • /natural sciences/computer and information sciences/artificial intelligence
  • /engineering and technology/medical engineering/diagnostic imaging/magnetic resonance imaging

Call for proposal

ERC-2020-STG
See other projects for this call

Funding Scheme

ERC-STG - Starting Grant

Host institution

UNIVERSITAET HAMBURG
Address
Mittelweg 177
20148 Hamburg
Germany
Activity type
Higher or Secondary Education Establishments
EU contribution
€ 1 499 129,03

Beneficiaries (1)

UNIVERSITAET HAMBURG
Germany
EU contribution
€ 1 499 129,03
Address
Mittelweg 177
20148 Hamburg
Activity type
Higher or Secondary Education Establishments